Interference minimized multipath routing with congestion control in wireless sensor network for multimedia streaming

INTERFERENCE-MINIMIZED MULTIPATH ROUTING WITH CONGESTION CONTROL IN WIRELESS SENSOR NETWORK FOR MULTIMEDIA STREAMING TEO JENN YUE BUGSY (B.Eng.(Hons.), NUS) A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF ENGINEERING DEPARTMENT OF ELECTRICAL & COMPUTER ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2007 Acknowledgements My sincere thanks go to my supervisor, Assistant Professor Ha Yajun I have enjoyed two fulfilling years doing research under his supervision He has imparted to me knowledge that is both practical and invaluable to my future endeovers He has also gone beyond his duties of a supervisor to act as a mentor and friend I would also like to thank my co-supervisor, Associate Professor Tham Chen Khong He has given me valuable advice and insight to the domain of wireless ad-hoc networking Without his advice and suggestions, this thesis would not have been possible I would also like to express my gratitude to my sponsoring company, DSO National Laboratories The DSO Postgraduate Scholarship has presented me the opportunity to obtain my Masters degree and also upgrade my technical knowledge and skills In addition, I would like to thank my bosses and colleagues in DSO, who have been encouraging and supportive during my studies In addition, I would like to thank Chee Seng and Say Huan for helping me in many ways Last but not least, I would like to give special thanks to my family, friends and anyone who is not mentioned here but had helped me in one way or another ii Contents Acknowledgements ii Table of Contents vi Abstract vii List of Figures x List of Tables xiii List of Abbreviations xiv Introduction 1.1 WSN Application and Network Architecture 1.2 Current Limitations 1.3 Proposed Solutions 1.4 Thesis Organization iii Background and Related Works 2.1 2.2 2.3 2.4 2.5 10 Routing Protocols 10 2.1.1 Ad-hoc On-demand Distance Vector (AODV) 11 2.1.2 Dynamic Source Routing (DSR) 12 Video-coding Techniques 12 2.2.1 Multiple Descriptions Coding (MDC) 13 Modeling Wireless Interferences 14 2.3.1 Protocol Model of Interference 15 2.3.2 Physical Model of Interference 16 Network Simulator 17 2.4.1 Global Mobile Systems Simulator (GloMoSim) 17 Review of Related Works 17 Modeling Multipath Load Balancing 21 3.1 General Communications Network 22 3.2 Wired Network 22 3.3 Wireless Network 24 3.3.1 Correlation Factor Metric 26 3.3.2 Conflict Graph 27 3.3.3 Proposed Technique 27 3.3.4 Illustrative Example 30 iv Interference-Minimized Multipath Routing (I2MR) Protocol 4.1 4.2 Problem Definition and Overview 35 4.1.1 Problem Definition 36 4.1.2 Protocol Overview 37 Protocol Details 38 4.2.1 Primary Path Discovery 38 4.2.2 Interference-Zone Marking 40 4.2.3 Secondary and Backup Path Discovery 42 Congestion Control Scheme for I2MR 5.1 5.2 35 47 Problem Definition and Overview 48 5.1.1 Problem Definition 48 5.1.2 Scheme Overview 49 Scheme Details 49 5.2.1 Detecting Long-term Path Congestions 50 5.2.2 Informing Source of Long-term Path Congestions 50 5.2.3 Reducing Loading Rate of Source 52 Experiments, Results and Discussions 55 6.1 Experimental Objectives 55 6.2 Simulation Model 60 6.3 Simulation Results and Discussions 63 v Conclusion, Limitations and Future Works 79 7.1 Summary of Results and Conclusion 79 7.2 Limitations and Future Works 81 Bibliography 82 vi Abstract Multimedia streaming in Wireless Sensor Network (WSN) is required for future military applications like battlefield surveillance to provide high-quality information of hot spots Although recent advances have enabled large-scale WSN to be deployed supported by high-bandwidth backbone network for multimedia streaming, the singlechannel and energy-constrained WSN still remains the bottleneck due to the lowrate radios used by the sensor nodes and the effects of wireless interferences that severely limit throughput Therefore, it is crucial to consider the effects of wireless interferences when using multipath load balancing Multipath load balancing can be used to increase throughput, but simply using link- or node-disjoint shortest paths is not sufficient to guarantee any throughput gains In order for multipath load balancing to be effective, shortest paths that are physically separated (i.e maximally zone-disjoint shortest paths) need to be discovered and used, so as to minimize the effects of wireless interferences However, discovering maximally zone-disjoint shortest paths without network-wide localization support or directional antennas is challenging and the problem is worse when nodes vii interfere beyond their communication ranges In this thesis, three contributions are made: First, a modeling technique for multipath load balancing is proposed The technique captures the effects of both interand intra-path wireless interferences using conflict graphs, without having to assume that nodes not interfere beyond their communication ranges A metric that can be used to evaluate the quality of a path-set for multipath load balancing is then derived from the conflict graphs Second, a heuristics-based Interference Minimized Multipath Routing (I2MR) protocol is proposed The protocol increases throughput by discovering and using maximally zone-disjoint shortest paths for load balancing, while requiring minimal localization support and incurring low routing overheads Furthermore, directional antennas are not used and nodes are assumed that they may interfere up to twice their communication ranges Third, a congestion control scheme for I2MR is proposed The scheme further increases throughput by dynamically reducing the load-rate of the source when longterm congestions are detected along the active paths used for load balancing The active paths are eventually loaded at the highest possible rate that can be supported, so as to minimize long-term path congestions Lastly, the proposed path-set evaluation technique is validated using GloMoSim simulations The proposed I2MR protocol with congestion control is also evaluated viii using simulations by comparing with the unipath Ad-hoc On-demand Distance Vector (AODV) protocol and the multipath Node Disjoint Multipath Routing (NDMR) protocol Simulation results show that I2MR with congestion control achieves on average 230% and 150% gains in throughput over AODV and NDMR respectively, and consumes comparable or at most 24% more energy than AODV but up to 60% less energy than NDMR ix List of Figures 1.1 Possible deployment scenario 1.2 Relaying target information to remote command center 1.3 Separation between paths due to magnetic repulsion 2.1 Multiple Descriptions Coding (MDC) 14 2.2 Geometric requirements for concurrent transmissions according to the protocol model of interference 16 3.1 Network topology 31 3.2 Connectivity graph G = (V, E) of network 32 3.3 Conflict graph H = (E, C) of network 33 4.1 Zone-disjoint paths from source to final destination 37 4.2 Broadcast RREQ algorithm Invoked when intermediate node i re- 4.3 ceives RREQ from node j 39 Marking sectors and overlapped regions 40 x be supported by the paths, resulting in the least congested paths for data transfer Increasing channel BER has little effect for both scenarios Figure 6.12 compares total energy consumed vs channel BER for both dense and less dense networks For the dense network in Figure 6.12(a), I2MR (CC) consumes comparable energy as AODV and approximately 60%, 50% and 5% lower energy than NDMR, I2MR50 and I2MR respectively For the less dense network in Figure 6.12(b), I2MR (CC) consumes at most 24% more energy than AODV and approximately 54%, 44% and 4% lower energy than NDMR, I2MR50 and I2MR respectively Total energy consumed for I2MR (CC) is the lowest compared to NDMR, I2MR50 and I2MR because it uses multipath load balancing with the largest inter-path separation, as total energy consumed decreases with increasing inter-path separation because of lower inter-path interferences With lower inter-path interferences, lesser packet retransmissions are incurred and data transfer can complete in a shorter time period, hence reducing the total energy consumed Increasing channel BER has little effect for both scenarios An interesting observation made is that although the aggregate throughputs for multipath schemes like NDMR, I2MR50, I2MR and I2MR (CC) are higher than the unipath scheme AODV as shown in Figure 6.10, the total energy consumed is larger for multipath schemes compared AODV There are three possible reasons: Firstly, the total energy consumed to discover a multipath path-set is much higher than that required for a single path as shown in Figure fig:graph energy pd Secondly, 72 14 AODV NDMR I2MR50 I2MR I2MR (CC) Average End-to-end Delay (103 secs ) 13 12 11 10 0.00E+00 1.00E-08 1.00E-07 1.00E-06 1.00E-05 Channel BER (a) 14 AODV NDMR I2MR50 I2MR I2MR (CC) Average End-to-end Delay (103 secs ) 13 12 11 10 0.00E+00 1.00E-08 1.00E-07 1.00E-06 1.00E-05 Channel BER (b) Figure 6.11: Average end-to-end delay vs channel BER for (a) dense network and (b) less dense network 73 more nodes are involved in data transfer for multipath schemes Lastly, although aggregate throughputs for multipath schemes are higher than AODV, individual path throughputs may not necessary be higher than AODV Figure 6.13 compares packet delivery ratio vs channel BER for both dense and less dense networks There is no significant degradation in performance for the less dense network and packet delivery ratios remain relatively constant as BER increases until it reaches 1.0E-5, where a slight drop is observed The packet delivery ratios for I2MR, I2MR50 and AODV are comparable and very close to 1, while packet delivery ratios for NDMR and I2MR (CC) are slightly lower For the case of NDMR, packets are lost due to severe inter-path interferences, resulting in the retransmission limits for intermediate nodes along the paths to be exceeded due to congestions For the case of I2MR (CC), packets are purged at the initial stages of data transfer when the source reduces its loading rate when long-term congestions occur Once the source eventually settles down at the highest possible rate supportable by the active paths, minimal packet losses are observed Lastly, the results that validates the proposed path-set evaluation technique are presented and discussed Figure 6.14 compares total interference correlation factor vs channel BER for both dense and less dense networks For the dense network in Figure 6.14(a), I2MR has the lowest total interference correlation factor, followed by I2MR50 and then NDMR, which has the highest total interference correlation factor For the less dense 74 28 26 24 Total energy consumed (KJ) 22 20 18 16 14 12 10 AODV NDMR I2MR50 I2MR I2MR (CC) 0.00E+00 1.00E-08 1.00E-07 1.00E-06 1.00E-05 Channel BER (a) 28 26 24 Total energy consumed (KJ) 22 20 18 16 14 12 10 AODV NDMR I2MR50 I2MR I2MR (CC) 0.00E+00 1.00E-08 1.00E-07 1.00E-06 1.00E-05 Channel BER (b) Figure 6.12: Total energy consumed vs channel BER for (a) dense network and (b) less dense network 75 1.05 Packet delivery ratio 0.95 0.9 AODV NDMR I2MR50 I2MR I2MR (CC) 0.85 0.8 0.00E+00 1.00E-08 1.00E-07 1.00E-06 1.00E-05 Channel BER (a) 1.05 Packet delivery ratio 0.95 0.9 AODV NDMR I2MR50 I2MR I2MR (CC) 0.85 0.8 0.00E+00 1.00E-08 1.00E-07 1.00E-06 1.00E-05 Channel BER (b) Figure 6.13: Packet delivery ratio vs channel BER for (a) dense network and (b) less dense network 76 network in Figure 6.14(b), I2MR also has the lowest total interference correlation factor, followed by I2MR50 and then NDMR, which has the highest total interference correlation factor Comparing I2MR, I2MR50 and NDMR, since I2MR achieves the lowest total interference correlation factor, followed by I2MR50 and then NDMR, therefore the aggregate throughput achieved by the path-set discovered by I2MR is expected to be the highest, followed by I2MR50 and then NDMR, which is expected to achieve the lowest aggregate throughput This is indeed the case as shown in Figure 6.10 77 140 130 Total Interference Correlation Factor 120 110 100 90 80 70 60 50 40 NDMR I2MR50 I2MR 30 20 10 0.00E+00 1.00E-08 1.00E-07 1.00E-06 1.00E-05 Channel BER (a) 140 Total Interference Correlation Factor 130 120 110 100 90 80 70 60 50 40 NDMR I2MR50 I2MR 30 20 10 0.00E+00 1.00E-08 1.00E-07 1.00E-06 1.00E-05 Channel BER (b) Figure 6.14: Total interference correlation factor vs channel BER for (a) dense network and (b) less dense network 78 Chapter Conclusion, Limitations and Future Works Chapter is organized as follow: Section 7.1 summarizes the experimental results obtained and then conclude Section 7.2 discusses possible limitations and suggests future works 7.1 Summary of Results and Conclusion Comparing the path discovery costs for I2MR, I2MR50, NDMR and AODV: The total path discovery time, total control bytes transmitted and total energy consumed during path discovery for I2MR is at least comparable or if not better than NDMR and not prohibitively larger than AODV and I2MR50 Although I2MR may transmit 79 more control packet than NDMR, but the size of the control packets for NDMR is significantly larger than I2MR, resulting in NDMR consuming more energy than I2MR during path discovery Comparing the path-set performances for I2MR (CC), I2MR, I2MR50, NDMR and AODV: I2MR using congestion control (i.e I2MR (CC)) achieves the highest throughput with up to 260%, 160%, 110% and 20% gains over AODV, NDMR, I2MR50 and I2MR respectively and the lowest average end-to-end delays Total energy consumed by I2MR (CC) is also the lowest among all the multipath schemes, up to 60%, 50% and 5% lower than NDMR, I2MR50 and I2MR respectively When compared with AODV, I2MR (CC) consumes comparable or at most 24% more energy I2MR (CC) also achieves acceptable packet delivery ratios with most packets losses occurring only in the initial stages of data transfer due to purging Comparing the quality of the path-sets for I2MR, I2MR50 and NDMR: The pathset discovered by I2MR has the lowest total interference correlation factor (i.e highest quality), followed by I2MR50 then NDMR, which has the highest total interference correlation factor (i.e lowest quality) Based on the results obtained, it can be concluded that: The proposed path-set evaluation technique for multipath load balancing is able capture both the effects of inter- and intra-path wireless interferences, while assuming that nodes may interfere beyond their communication ranges Furthermore, the derived total interference correlation factor metric can be used 80 to evaluate the quality of a path-set discovered for multipath load balancing The proposed I2MR protocol is able to significanly increase throughput by discovering and using maximally zone-disjoint shortest paths for load balancing, while requiring minimal localization support and incurring low overheads Furthermore, directional antennas are not used and nodes may interfere up to twice their communication ranges The propose congestion control scheme is able further increase throughput by loading the active paths at the highest possible rate that can be supported, so as to minimize long-term path congestions 7.2 Limitations and Future Works A possible limitation of the proposed I2MR protocol is that the wireless interferences between neighboring path-sets used by different source-final destination pairs require the deployment of these pairs to be suitably spaced-out For future works, we hope to extend the proposed I2MR protocol to take into account the effects of inter path-set interferences, so as to ease the deployment of the WSN 81 Bibliography [1] Stephen Mueller, Rose P Tsang, and Dipak Ghosal Multipath routing in mobile ad hoc networks: Issues and challenges In MASCOTS Tutorials, pages 209–234, 2003 [2] E P C Jones, M Karsten, and P A S Ward Multipath load balancing in multi-hop wireless networks Wireless And Mobile Computing, Networking And Communications, 2005 (WiMob’2005), IEEE International Conference on, 2:158–166 Vol 2, 2005 [3] Kamal Jain, Jitendra Padhye, Venkata N Padmanabhan, and Lili Qiu Impact of interference on multi-hop wireless network performance In MobiCom ’03: Proceedings of the 9th annual international conference on Mobile computing and networking, pages 66–80, New York, NY, USA, 2003 ACM Press [4] Shree Murthy and J J Garcia-Luna-Aceves An efficient routing protocol for wireless networks Mob Netw Appl., 1(2):183–197, 1996 82 [5] Charles E Perkins and Pravin Bhagwat Highly dynamic destination-sequenced distance-vector routing (dsdv) for mobile computers In SIGCOMM ’94: Proceedings of the conference on Communications architectures, protocols and applications, pages 234–244, New York, NY, USA, 1994 ACM Press [6] Charles E Perkins and Elizabeth M Royer Ad-hoc on-demand distance vector routing In WMCSA ’99: Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications, page 90, Washington, DC, USA, 1999 IEEE Computer Society [7] David B Johnson and David A Maltz Dynamic source routing in ad hoc wireless networks In Imielinski and Korth, editors, Mobile Computing, volume 353 Kluwer Academic Publishers, 1996 [8] Vivek K Goyal Multiple description coding: Compression meets the network IEEE Signal Processing Magazine, 18(5):74–93, September 2001 [9] Y Wang, S Panwar, S Lin, and S Mao Wireless video transport using path diversity: multiple description vs layered coding In Proc IEEE Int Conf on Image Proc., Rochester, USA, September 2002 [10] Xiang Zeng, Rajive Bagrodia, and Mario Gerla Glomosim: a library for parallel simulation of large-scale wireless networks In PADS ’98: Proceedings of the twelfth workshop on Parallel and distributed simulation, pages 154–161, Washington, DC, USA, 1998 IEEE Computer Society 83 [11] Mario Gerla and Kaixin Xu Multimedia streaming in large-scale sensor networks with mobile swarms SIGMOD Rec., 32(4):72–76, 2003 [12] Sung-Ju Lee and Mario Gerla Aodv-br: Backup routing in ad hoc networks In Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC 2000), Chicago, IL, Sepember 2000 [13] Xuefei Li and Laurie Cuthbert A reliable node-disjoint multipath routing with low overhead in wireless ad hoc networks In MSWiM ’04: Proceedings of the 7th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems, pages 230–233, New York, NY, USA, 2004 ACM Press [14] M Marina and S Das On-demand multipath distance vector routing in ad hoc networks In ICNP ’01: Proceedings of IEEE International Conference on Network Protocols, pages 14–23, 2001 [15] Jinyang Li, Charles Blake, Douglas S J De Couto, Hu Imm Lee, and Robert Morris Capacity of ad hoc wireless networks In Mobile Computing and Networking, pages 61–69, 2001 [16] Marc R Pearlman, Zygmunt J Haas, Peter Sholander, and Siamak S Tabrizi On the impact of alternate path routing for load balancing in mobile ad hoc networks In MobiHoc ’00: Proceedings of the 1st ACM international symposium on Mobile ad hoc networking & computing, pages 3–10, Piscataway, NJ, USA, 2000 IEEE Press 84 [17] P Pham and S Perreau Multi-path routing protocol with load balancing policy in mobile ad hoc network Mobile and Wireless Communications Network, 2002 4th International Workshop on, pages 48–52, 2002 [18] Ren Xiuli and Yu Haibin A novel multipath disjoint routing to support ad hoc wireless sensor networks In ISORC ’06: Proceedings of the Ninth IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC’06), pages 174–178, Washington, DC, USA, 2006 IEEE Computer Society [19] Kui Wu and Janelle Harms Performance study of a multipath routing method for wireless mobile ad hoc networks In MASCOTS ’01: Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS’01), page 99, Washington, DC, USA, 2001 IEEE Computer Society [20] Gang Zhou, Tian He, Sudha Krishnamurthy, and John A Stankovic Impact of radio irregularity on wireless sensor networks In MobiSys ’04: Proceedings of the 2nd international conference on Mobile systems, applications, and services, pages 125–138, New York, NY, USA, 2004 ACM Press [21] Nam T Nguyen, An-I Andy Wang, Peter Reiher, and Geoff Kuenning Electricfield-based routing: a reliable framework for routing in manets SIGMOBILE Mob Comput Commun Rev., 8(2):35–49, 2004 85 [22] Siuli Roy, Somprakash Bandyopadhyay, Tetsuro Ueda, and Kazuo Hasuike Multipath routing in ad hoc wireless networks with omni directional and directional antenna: A comparative study In IWDC ’02: Proceedings of the 4th International Workshop on Distributed Computing, Mobile and Wireless Computing, pages 184–191, London, UK, 2002 Springer-Verlag [23] Siuli Roy, Dola Saha, S Bandyopadhyay, Tetsuro Ueda, and Shinsuke Tanaka A network-aware mac and routing protocol for effective load balancing in ad hoc wireless networks with directional antenna In MobiHoc ’03: Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing, pages 88–97, New York, NY, USA, 2003 ACM Press 86 [...]... channel wireless network, the effects of wireless interferences need to be factored into the problem formulation Wireless interferences in a wireless network can be modeled using either by the 1) protocol model of interference or 2) physical model of interference [3] The protocol model of interference models interference in a binary manner, which means that any signal in the presence of interferences... between source and destination nodes Two main classes of routing protocols are table-based and on-demand protocols In table-based protocols [4,5], each node maintains a routing table containing routes to all nodes in the network Nodes must periodically exchange messages 10 with routing information to keep routing tables up-to-date However table-based routing protocols are impractical for the large-scale... effects of both inter- and intra-path wireless interferences It can be used to evaluate the quality of a path-set discovered for multipath load balancing 6 The second contribution is to propose a heuristics-based Interference- Minimized Multipath Routing (I2MR) protocol that increases throughputs by discovering and using maximally zone-disjoint shortest paths for load balancing, while requiring minimal localization... largescale WSN with high-capacity UAV backbone network support for multimedia streaming, however multipath routing is not used Much research has been done on multipath 17 routing for multi-hop and single-channel wireless networks, promising many benefits over unipath routing [1] Many such works [12–14] discover multiple link- or nodedisjoint paths, but use only the best path for data transfer, switching to... protocol model of interference and also that it represents the worst cast effects of wireless interferences, it will be used to model wireless interferences when analyzing the problem of multipath load balancing in a single channel wireless network for this thesis Both the protocol model of interference and physical model of interference are briefly described below 2.3.1 Protocol Model of Interference The... relevant background information, while Section 2.5 reviews related works on multipath load balancing For background information: Section 2.1 reviews routing protocols, Section 2.2 describes video-coding techniques, Section 2.3 presents models for wireless interferences and Section 2.4 describes the network simulator used 2.1 Routing Protocols Routing protocols are used to find and maintain routes between... using multiple node-disjoint shortest paths in a single-channel wireless network results in negligible benefits due to severe route coupling Several works [17, 18] modify the DSR protocol for multipath load balancing, naively using multiple node-disjoint shortest paths Their results show slight improvements in performance over unipath routing, suggesting the possibility of an interference- aware multipath. .. Section 3.2 describes the technique used for modeling multipath load balancing in a wired network For Section 3.3: Sections 3.3.1 and 3.3.2 describe the technique used for modeling multipath routing in a wireless network, Section 3.3.3 presents the proposed technique used to evaluate the quality of a path-set discovered for multipath load balancing in a wireless network and Section 3.3.4 provides an example... RATE DCF DISTRIBUTED COORDINATION FUNCTION DSR DYNAMIC SOURCE ROUTING EO ELECTRO-OPTIC GLOMOSIM GLOBAL MOBILE SYSTEMS SIMULATOR I2MR INTERFERENCE- MINIMIZED MULTIPATH ROUTING IZ INTERFERENCE ZONE LC-ARQ LAYERED-CODING WITH SELECTIVE ARQ MAC MEDIUM ACCESS CONTROL MDC MULTIPLE DESCRIPTIONS CODING MDMC MULTIPLE DESCRIPTIONS MOTION COMPENSATION xiv NDMR NODE-DISJOINT MULTIPATH ROUTING RREP ROUTE REPLY RREQ... hop-by-hop routing by maintaining routing table entries at intermediate nodes The route discovery process is initiated when a source needs a route to a destination and it does not have a route in its routing table The source floods the network with a route request (RREQ) packet specifying the destination requested When the destination node receives the RREQ packet, it replies the source with a route ... exchange messages 10 with routing information to keep routing tables up-to-date However table-based routing protocols are impractical for the large-scale and energy-constrained WSN In on-demand protocols... WSN with high-capacity UAV backbone network support for multimedia streaming, however multipath routing is not used Much research has been done on multipath 17 routing for multi-hop and single-channel... SYSTEMS SIMULATOR I2MR INTERFERENCE- MINIMIZED MULTIPATH ROUTING IZ INTERFERENCE ZONE LC-ARQ LAYERED-CODING WITH SELECTIVE ARQ MAC MEDIUM ACCESS CONTROL MDC MULTIPLE DESCRIPTIONS CODING MDMC MULTIPLE